Chapter 6: Functions

Defining Functions

A function is like a "vending machine" — you insert input (parameters) and it outputs a result (return value). Wrapping repeated code into functions makes your code cleaner.

# Basic function definition
def greet(name):
    """Say hello to someone (this is a docstring)"""
    return f"Hello, {name}! Welcome to Python!"

message = greet("Alice")
print(message)

# View the docstring
print(greet.__doc__))

Hello, Alice! Welcome to Python!
Say hello to someone (this is a docstring)

Parameter Types In-Depth

# 1. Positional parameters
def add(a, b):
    return a + b

print(f"10 + 20 = {add(10, 20)}")

# 2. Keyword parameters (can be passed in any order)
def profile(name, age, city):
    return f"{name}, {age} years old, from {city}"

print(profile(age=25, city="Beijing", name="Bob"))

# 3. Default parameters
def power(base, exponent=2):
    return base ** exponent

print(f"2 to the power of 3 = {power(2, 3)}")
print(f"5 squared = {power(5)}")  # Uses default value

# 4. Variable-length args *args (packs into a tuple)
def total(*args):
    print(f"  Received args: {args}")
    return sum(args)

print(f"Sum = {total(1, 2, 3, 4, 5)}")

# 5. Keyword variable-length args **kwargs (packs into a dict)
def show_info(**kwargs):
    for key, value in kwargs.items():
        print(f"  {key}: {value}")

show_info(name="Alice", age=18, hobby="Coding")

10 + 20 = 30
Bob, 25 years old, from Beijing
2 to the power of 3 = 8
5 squared = 25
  Received args: (1, 2, 3, 4, 5)
Sum = 15
  name: Alice
  age: 18
  hobby: Coding

Lambda Anonymous Functions

# lambda is a one-line mini function
square = lambda x: x ** 2
print(f"3 squared = {square(3)}")

# Commonly used with sorted, map, filter, etc.
students = [("Alice", 85), ("Bob", 92), ("Charlie", 78)]

# Sort by score
sorted_students = sorted(students, key=lambda s: s[1], reverse=True)
print(f"Score ranking: {sorted_students}")

# map: apply function to each element
numbers = [1, 2, 3, 4, 5]
doubled = list(map(lambda x: x * 2, numbers))
print(f"Doubled: {doubled}")

# filter: filter elements
evens = list(filter(lambda x: x % 2 == 0, numbers))
print(f"Even numbers: {evens}")

3 squared = 9
Score ranking: [('Bob', 92), ('Alice', 85), ('Charlie', 78)]
Doubled: [2, 4, 6, 8, 10]
Even numbers: [2, 4]

Decorators

A decorator is like "getting dressed" for a function — it doesn't change the function itself but adds extra features (like timing, logging, or permission checks).

import time

# Define a timer decorator
def timer(func):
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        elapsed = time.time() - start
        print(f"  ⏱️ {func.__name__} took: {elapsed:.4f}s")
        return result
    return wrapper

# Use decorator with @ syntax
@timer
def slow_function(n):
    """An intentionally slow function"""
    total = 0
    for i in range(n):
        total += i
    return total

result = slow_function(1_000_000)
print(f"Result: {result}")

⏱️ slow_function took: 0.0512s
Result: 499999500000